∗ 2014 – Eindhoven Train Station

Location Main walkway, Eindhoven Train Station (2014-2015 config)
Aim Study diluted and dense pedestrian dynamics
Recorded Area 2.3m (L) x 9 m (W) / 4 Kinect sensors
Processing Offline, 24/7 recording, 100GB/day
Data 100.000 trajectories per day/5M trajectories in total

To investigate diluted and denser crowding conditions with higher statistics we expanded our tracking system to cover the whole width of the main corridor of Eindhoven Train Station. We employed a grid of four sensors. 

 

 

Acquisition system with four Kinect sensors
The four signals are merged after the perspective view is undistorted

 

Below some example of the trajectories obtained (Click here for videos ) 

 

The following publications include technological details, density and direction ratio conditioned fundamental diagrams and data analytics approaches.

2018

Alessandro Corbetta, Jasper Meeusen, Chung-min Lee, Roberto Benzi, Federico Toschi

Physics-based modeling and data representation of pairwise interactions among pedestrians Journal Article

Physical Review E, 98 , pp. 062310, 2018.

Links | BibTeX

2017

Alessandro Corbetta; Federico Toschi

Overhead pedestrian tracking for large scale real-life crowd dynamics analyses Incollection

Enrico Ronchi (Ed.): New approaches to evacuation modelling, pp. 40-51, Lund University Fire Safety Engineering Report, 2017.

Abstract | Links | BibTeX

2016

Jasper Meeusen

Dense Crowd Dynamics Masters Thesis

Eindhoven University of Technology, 2016.

Abstract | BibTeX

Alessandro Corbetta; Chung-min Lee; Jasper Meeusen; Federico Toschi

Continuous measurements of real-life bidirectional pedestrian flows on a wide walkway Inproceedings

Proceedings of Pedestrian and Evacuation Dynamics 2016, pp. 18-24, 2016.

Abstract | Links | BibTeX

Alessandro Corbetta

Multiscale crowd dynamics: physical analysis, modeling and applications PhD Thesis

Eindhoven University of Technology, 2016.

Abstract | Links | BibTeX